a. Technical Field
The present disclosure relates to a system and method for capturing images used in facial recognition systems. In particular, the present disclosure relates to a system and method that capture a series of images using different exposure times in accordance with a predetermined profile to generate one or more usable images despite variations in skin tone and/or available light.
b. Background
Biometric technologies are now extensively used to identify and authenticate individuals in a variety of fields such as forensics, immigration control, payment systems, and access control. One biometric technology that is growing in use is facial recognition. In facial recognition systems, a probe image of the face of an individual is captured and then compared to one or more previously obtained gallery images in a gallery database for purposes of identification or authentication. The facial recognition system identifies a face in the probe image, identifies key facial features such as the positions of the eyes (including the iris), nose, ears, mouth, chin and head and creates a facial template. This template is compared against templates for each of the gallery images to generate similarity scores indicative of a potential match.
The effectiveness of facial recognition systems is dependent on, among other things, capturing quality images of an individual's face. Unfortunately, probe and gallery images are generally obtained in an uncontrolled environment with many variables including lighting, shadows, camera characteristics, movement and/or the orientation of an individual, and the age or ethnicity of an individual. For example, the amount of natural or artificial lighting on the face of the individual can vary widely depending on the time of day, weather conditions and the functioning of artificial light sources. The variation in illumination affects image quality. Both low levels of illumination and high levels of illumination (image saturation) obscure facial features used for identification and authentication. An ideal illumination level for facial recognition is between about 600 lux to about 1000 lux. On a dark night, illumination may be as small as a fraction of one lux. On a clear day, bright sunlight can result in illumination on the order of a hundred thousand lux. Even when the amount of light is constant, variations in skin tone can affect image quality. Oily skin or pale skin tones will produce different images relative to dark skin tones and it is therefore difficult to assure quality images for all individuals even when the amount of light does not vary. Poor quality probe or gallery images can result in false positives (i.e., that a match exists between a probe image and a gallery image) or false negatives (i.e., that there is no match between the probe image and any gallery image) and can therefore render facial recognition systems unreliable.
Some facial recognition systems attempt to address image quality by modifying algorithms to account for specific environmental variables. This approach, however, is not generally applicable to systems employing different proprietary face detection algorithms. Other facial recognition systems attempt to address image quality by taking a larger number of images by, for example, processing a short video clip, and identifying the image having the best quality. Although this process can address some environmental variables (e.g., movement of the individual), it fails to address many other variables that may remain substantially constant over a period of time such as the amount of light on the face of the individual or the individual's skin tone.
The inventors herein have recognized a need for a system and method for capturing images used in facial recognition systems that will reduce or eliminate one or more of the above-identified deficiencies and/or provide improved performance.